期刊
CLINICAL NEUROPHYSIOLOGY
卷 125, 期 7, 页码 1392-1399出版社
ELSEVIER IRELAND LTD
DOI: 10.1016/j.clinph.2013.11.022
关键词
rTMS; EEG; Signal processing; Personalized medicine; Depression; Non-linear analysis; Lempel-Ziv complexity
Objective: Several linear electroencephalographic (EEG) measures at baseline have been demonstrated to be associated with treatment outcome after antidepressant treatment. In this study we investigated the added value of non-linear EEG metrics in the alpha band in predicting treatment outcome to repetitive transcranial magnetic stimulation (rTMS). Methods: Subjects were 90 patients with major depressive disorder (MDD) and a group of 17 healthy controls (HC). MDD patients were treated with rTMS and psychotherapy for on average 21 sessions. Three non-linear EEG metrics (Lempel-Ziv Complexity (LZC); False Nearest Neighbors and Largest Lyapunov Exponent) were applied to the alpha band (7-13 Hz) for two 1-min epochs EEG and the association with treatment outcome was investigated. Results: No differences were found between a subgroup of unmedicated MDD patients and the HC. Nonresponders showed a significant decrease in LZC from minute 1 to minute 2, whereas the responders and HC showed an increase in LZC. Conclusions: There is no difference in EEG complexity between MDD and HC and the change in LZC across time demonstrated value in predicting outcome to rTMS. Significance: This is the first study demonstrating utility of non-linear EEG metrics in predicting treatment outcome in MDD. (C) 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
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